%0 Journal Article
%T Research on text hierarchical clustering algorithm based on K-Means<br>基于KMeans的文本层次聚类算法研究
%A YU Jing-hui
%A HE Pi-lian
%A SUN Yue-heng
%A <br>尉景辉
%A 何丕廉
%A 孙越恒
%J 计算机应用
%D 2005
%I 
%X A new text hierarchical clustering algorithm based on K-Means was presented, which combined features from both K-Means and agglomerative approach that allowed them to reduce the early-stage errors made by agglomerative method and hence improved the quality of clustering solutions. The experimental evaluation shows that, our algorithm leads to better solutions than agglomerative methods.
%K text clustering
%K vector space model
%K K-Means
%K hierarchical clustering<br>文本聚类
%K 向量空间模型
%K K-Means算法
%K 层次聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=19FA503FC75C4DD1&yid=2DD7160C83D0ACED&vid=C5154311167311FE&iid=F3090AE9B60B7ED1&sid=44150A7B97EFCCE6&eid=F728FC2D3A6F8DAF&journal_id=1001-9081&journal_name=计算机应用&referenced_num=3&reference_num=8